Muhammad Asif Nauman*, Muhammad Shoaib
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 925-939, 2022, DOI:10.32604/cmc.2022.022147
Abstract Real time crowd anomaly detection and analyses has become an active and challenging area of research in computer vision since the last decade. The emerging need of crowd management and crowd monitoring for public safety has widen the countless paths of deep learning methodologies and architectures. Although, researchers have developed many sophisticated algorithms but still it is a challenging and tedious task to manage and monitor crowd in real time. The proposed research work focuses on detection of local and global anomaly detection of crowd. Fusion of spatial-temporal features assist in differentiation of feature trained using Mask R-CNN with Resnet101… More >
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